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CoderGnome (talk | contribs) →Variations and practicalities: Added a reason for the repulsion force in repulsive PSO. |
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* <math> x_{i,j} \leftarrow x_{i,j} + v_{i,j}.</math>
In Standard PSO (available on the Particle Swarm Central, see the external link below), the parameter <math> c_1 </math> is set to zero. And when <math> neighborhood best_j = local best_{i,j} </math>, then <math> r_3 </math> is also (temporarily) set to zero.
As the swarm iterates, the fitness of the global best solution improves (decreases for minimization problem). It could happen that all particles being influenced by the global best eventually approach the global best, and from there on the fitness never improves despite however many runs the PSO is iterated thereafter. The particles also move about in the search space in close proximity to the global best and not exploring the rest of search space. This phenomenon is called 'convergence'. If the inertial coefficient of the velocity is small, all particles could slow down until they approach zero velocity at the global best. The selection of coefficients in the velocity update equations affects the convergence and the ability of the swarm to find the optimum. One way to come out of the situation is to reinitialize the particles positions at intervals or when convergence is detected.
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